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Half-life of knowledge. Hari V Sahasrabuddhe Kanwal Rekhi School of I.T., IITB hvs@it.iitb.ac.in. what is half-life?.

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Half-life of knowledge

Hari V Sahasrabuddhe

Kanwal Rekhi School of I.T., IITB


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what is half-life?

Definition: The time required for the quantity of a chemical, drug or radioisotope to fall to half. For example, if the quantity now is 32, and half-life is 10 days, the quantity will be 16 after 10 days, 8 after 10 more days, etc.

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Does knowledge decay like that?

No, but it may become useless when the situation changes

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A progression of terms

  • Data: factual information, often numeric

  • Information: specific knowledge

  • Knowledge: familiarity, awareness, understanding

  • Wisdom: insight, ability to judge

    Our use of “knowledge” is a bit fuzzy – it fits somewhere in this progression.

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What is new in Oracle9i?

  • Oracle Streams (replace Oracle Advance Replication and Standby Databases)

  • Cluster file system for Windows and Linux (raw devices are no longer required)

  • (etc.)

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MySQL: Changes in 5.0.2

Warning: Incompatible change!NOT a BETWEEN b AND c is parsed as NOT (a BETWEEN b AND c) rather than as (NOT a) BETWEEN b AND c

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Even mathematics!

Is mathematics necessary? Moving Beyond Myths, published by the National Academy of Sciences, says so, but Prof. Dudley of DePauw University does not agree!

(See references)

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Halting problem - definition

Given a description of an algorithm and its initial input, determine whether the algorithm, when executed on this input, ever halts (completes). The alternative is that it runs forever without halting.

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Halting problem - answer

Alan Turing proved in 1936 that a general algorithm to solve the halting problem for all possible inputs cannot exist. We say that the halting problem is undecidable.

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Halting problem – informal proof

  • Let P be a program that reads any program Q and prints 1 if Q halts, 0 if not.

  • Define P’:

    • read program Q

    • simulate P on input Q

    • if output of step 2 is = 1, go to step 2

    • Halt

  • What happens when P’ is fed to P’?

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Halting problem – formal proof

Turing’s formal proof is based on Turing Machine, a model of computation with a finite controller coupled to a unbounded memory

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Another model of computation


  • Allows us to define a recursive function

  • Foundation for LISP class of programming languages

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Decidable but hard problems

  • Hamiltonian circuit: a circuit that visits all vertices of a given graph

  • We don’t know how to find one in any arbitrary graph in time limited by a polynomial, any polynomial, of the number of vertices.

  • If you can solve that one, a number of other problems are solved!

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Hard - example

  • Remember Cramer’s rule?

    n*n determinant => n (n-1)*(n-1) determinants

  • Time for n*n determinant equals roughly n*time for an (n-1)*(n-1) determinant

  • A PC which can calculate a 2*2 determinant in 0.5*10-9 seconds needs almost 1 year to calculate a 19*19 determinant by Cramer’s rule, and 19 years for a 20*20 determinant!

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Hard example contd.

  • We could use a supercomputer. A 60 teraflop supercomputer can calculate a 19*19 determinant in less than 17 hours (but even it will need about 18 years for a 22*22 determinant)

  • So, faster computers do not compensate for algorithmic complexity

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First programmer

Charles Babbage described his analytical engine in 1834, and in 1842-43 Lady Lovelace either created or corrected a program for it to computeBernoulli numbers(first defined in print in 1713)

(The analytical enginecould never actually be built.)

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How many programming languages are there?

  • Thousands of them!

  • Main types

    • Imperative (c, c++, java, …)

    • Functional (LISP, SCHEME) and applicative (APL)

    • Declarative (PROLOG)

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BCS: Future challenges

Conference: Brit. Comp. Soc., 29-31 March 2004

  • Two separate reports, on “Grand Challenges” in education and research

  • Either report identifies seven challenges

  • Most challenges arisefrom spread of computing to new areas, e.g. embedded systems, memories for life

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Identifying lasting knowledge

  • Abstract rather than concrete

    • Technology-independent areas, e.g. maths, theoretical CS, architecture, …

  • Older, still useful knowledge

    • (if it survived n years it might survive n more years)

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What after you graduate?

  • Self-study and reference skills

    • library, bookstores, search engines, …

  • List of references is available

    • These were gathered using web search